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Software used to store time-stamped data for monitoring and analysis. - Capture chronological data points in real time with associated values and timestamps - Record data streams from IoT devices, monitor application performance, or use other trends from temporal ordering - Use key index of time to understand changes in continually produced data
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Enables developers and data scientists with an enterprise ready time series data analytics engine for MLOps, AI and other data-driven workloads. Also available on the Microsoft Azure Marketplace. - Built on kdb+ - Multi-cloud, hybrid and on prem - Elastic scalability - IAM & Auth - Friendly UI + q, SQL & Python
InfluxDB is the leading time series database purpose-built to manage all types of time series data – metrics, events, traces – in a single datastore. Designed to handle high-speed, high-volume, and high-cardinality data, InfluxDB enables real-time insights and analysis.
QuasarDB is a time-series database optimized for large volumes and low latency. It combines the speed of an in-memory database with the yield of data warehouses. Quasar is designed from the ground up to power real-time intel. Ingest more. Compress better. Query faster. Use fewer resources. Spend less.
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QuestDB is the fastest open source time series database
The open IIoT platform for Industry 4.0 Factry Historian is a powerful and easy-to-use IIoT data management platform for collecting, storing and visualising industrial process data. Our historian software will enable your business to transform raw production data into actionable visual insights, drastically reduce downtime, avoid costs and drive a better overall plant performance. Use our Event Module to get deeper data insights and save time on reporting: Add context to raw production data with Factry Historian's event detection and analysis module. Automatically aggregate raw process data in the context of specific events, such as orders, products, batches, or downtime.
Shakti is a parallel data platform that merges analytics and database into one. It is used for extremely fast, complex analytics on data at scale. Shakti is the latest evolution of a foundational computing approach which operates on entire lists of data concurrently. Its architecture makes it a powerful tool for programmers to maximize the performance of both the software and the hardware they use for time-series and heterogenous data challenges.